a. Field of the Invention
This disclosure relates generally to systems and methods for generating a multi-dimensional model of a geometric structure. More particularly, this disclosure relates to a computer-implemented system and method for generating a multi-dimensional model of a geometric structure, such as, for example, an intra-cardiac structure, from a plurality of individual surface models corresponding to different regions of the geometric structure that are joined together to form a single composite surface model.
b. Background Art
It is known that various computer-based systems and computer-implemented methodologies can be used to generate multi-dimensional surface models of geometric structures, such as, for example, anatomic structures. More specifically, a variety of systems and methods have been used to generate multi-dimensional surface models of the heart and/or particular portions thereof.
One conventional methodology or technique involves the generation of a plurality of individual surface models corresponding to different regions of interest of a particular structure, and then joining the individual surface models together to form a single composite multi-dimensional surface model. It is known to generate the individual surface models by collecting location data points from the surfaces of the respective regions of interest and then using those location data points to generate an individual surface model for each region of interest.
Any number of techniques can be used to generate the individual surface models from the respective location data points, including, for example, convex hull, star-shaped domain approximation, and alpha-shape techniques. Once the individual surface models are generated, they are joined together to form a single composite surface model. One known way by which the individual surface models may be joined is by performing a Boolean operation (e.g., using a Boolean Union technique).
Conventional techniques for generating composite surface models from multiple individual surface models generated using collections of location data points are not without their drawbacks, however. For example, composite surface models formed by joining individual surface models generated using collections of location data points may not generate the most accurate representation of the structure of interest. For instance, the individual surface models may not reflect the corresponding region of interest with a desired degree detail or accuracy, or the individual surface models may be less than ideal for multi-dimensional Boolean operations. Either one of these drawbacks may result in a composite surface model that does not reflect the structure of interest with the desired degree of accuracy.
More particularly, while techniques like the convex hull and star shaped domain approximation techniques may provide water-tight surfaces suitable for multi-dimensional Boolean operations, the models produced using these techniques may contain false positive volumes that misrepresent the actual region where the location data points are collected. Therefore, composite surface models comprised of individual surface models generated using these techniques may not have the degree of accurateness or detail that is desired.
Similarly, while techniques like the alpha-shape technique may provide more accurate approximations of the region where location data points are collected as compared to either the convex hull or star-shaped domain approximation, the individual surface models produced using this technique may provide surfaces that are open and non-manifold. As such, the individual surface models generated using this type of technique are less than ideal for multi-dimensional Boolean operations, and require additional processing to account for the non-manifold surfaces in the generation of an acceptable composite surface model.
Thus, composite surface models that are formed, in essence, using collections of location data points, may not provide the desired degree of accuracy and/or may require an undesirable amount of additional processing that increases the complexity of, and the length of time required to perform, the composite surface model generation process.
Accordingly, the inventors herein have recognized a need for a system and method for generating a multi-dimensional model of a geometric structure that will minimize and/or eliminate one or more of the deficiencies in conventional systems.